The Problem of Object Recognition in the Presence of Noise in Original Data

被引：0

作者：

Vagin, V. N. ^{[1
]}

Fomina, M. V. ^{[1
]}

Kulikov, A. V. ^{[1
]}

机构：

[1] Tech Univ, Moscow Power Engn Inst, Moscow 111250, Russia

来源：

TENTH SCANDINAVIAN CONFERENCE ON ARTIFICIAL INTELLIGENCE | 2008年 / 173卷

关键词：

knowledge acquisition and discovery; data mining; rough sets; decision tree; noise model; learning sample;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The problem of object generalization with account for the necessity of processing the incomplete and inconsistent information stored in real databases is considered. It is suggested to use means of rough sets theory and decision trees to generalize the information stored in real databases. Noise models are presented, and a noise effect on the operation of generalization algorithms using the methods of building decision trees is developed. The algorithm for unknown values reconstruction in learning samples subjected to the noise effect based on the nearest neighbour method is proposed. The results of program modeling are brought out.

引用

页码：60 / 67

页数：8

共 50 条

[41] Mining the Statistical Information of Confidential Data from Noise-Multiplied Data [J].

Lin, Yan-Xia .

2017 IEEE 15TH INTL CONF ON DEPENDABLE, AUTONOMIC AND SECURE COMPUTING, 15TH INTL CONF ON PERVASIVE INTELLIGENCE AND COMPUTING, 3RD INTL CONF ON BIG DATA INTELLIGENCE AND COMPUTING AND CYBER SCIENCE AND TECHNOLOGY CONGRESS(DASC/PICOM/DATACOM/CYBERSCI, 2017, :1292-1297

[42] Limitations with Activity Recognition Methodology & Data Sets [J].

Lockhart, Jeffrey W. ;

Weiss, Gary M. .

PROCEEDINGS OF THE 2014 ACM INTERNATIONAL JOINT CONFERENCE ON PERVASIVE AND UBIQUITOUS COMPUTING (UBICOMP'14 ADJUNCT), 2014, :747-756

[43] Microarrays, pattern recognition and exploratory data analysis [J].

Mertens, BJA .

STATISTICS IN MEDICINE, 2003, 22 (11) :1879-1899

[44] Attention-Based Neural Network for Erratic Noise Attenuation From Seismic Data With a Shuffled Noise Training Data Generation Strategy [J].

Wang, Shaowen ;

Song, Peng ;

Tan, Jun ;

He, Bingshou ;

Wang, Qianqian ;

Du, Guoning .

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 60

[45] Using data mining techniques for exploring learning object repositories [J].

Segura, Alejandra ;

Vidal-Castro, Christian ;

Menendez-Dominguez, Victor ;

Campos, Pedro G. ;

Prieto, Manuel .

ELECTRONIC LIBRARY, 2011, 29 (02) :162-180

[46] OBJECT ORIENTED AGGLOMERATIVE HIERARCHICAL CLUSTERING MODEL IN DATA MINING [J].

Yesilbudak, Mehmet ;

Kahraman, Hamdi Tolga ;

Karacan, Hacer .

JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITY, 2011, 26 (01) :27-39

[47] An outlier detection algorithm for categorical matrix-object data [J].

Cao, Fuyuan ;

Wu, Xiaolin ;

Yu, Liqin ;

Liang, Jiye .

APPLIED SOFT COMPUTING, 2021, 104

[48] Exploring Data Mining Possibilities on Computer Based Problem Solving Data [J].

Pejic, Aleksandar ;

Molcer, Piroska Stanic .

2016 IEEE 14TH INTERNATIONAL SYMPOSIUM ON INTELLIGENT SYSTEMS AND INFORMATICS (SISY), 2016, :171-175

[49] An efficient technique for object recognition using Shi-Tomasi corner detection algorithm [J].

Bansal, Monika ;

Kumar, Munish ;

Kumar, Manish ;

Kumar, Krishan .

SOFT COMPUTING, 2021, 25 (06) :4423-4432

[50] Research on application of data mining in fast character recognition based on big data [J].

Zheng, Ying ;

Song, Wangan ;

Shen, Longfeng .

CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2018, 30 (24)

← 1 2 3 4 5 →